Department of Artificial Intelligence and Machine Learning(AI & ML)

B.Tech. CSE with specialization in AI & ML

An “intelligent” computer uses Artificial Intelligence to think like a human and perform tasks on its own. Machine Learning is how a computer system develops its intelligence.

The major industries using Artificial Intelligence (AI) and Machine Learning (ML) include Agriculture, Education and Infrastructure, Healthcare, Transport, Banking, Cyber Security, Manufacturing, Entertainment, Hospitality, and others.

Keeping in view making the students meet the industry needs, Godavari Institute of Engineering and Technology (GIET), Rajahmundry, an Autonomous Institution brought up B.Tech. In Computer Science & Engineering with specialization in Artificial Intelligence and Machine Learning. Admissions to this specialization program will be granted to the best brains that have an excellent score in APEAPCET.

B.Tech in CSE with AI & ML as its specialization is encompassed with comprehensive and rigorous curriculum covering key concepts and technologies of Artificial Intelligence and Machine Learning. It presents a solid foundation in the principles and technologies that underlie many facets of AI, including logic, knowledge representation, probabilistic models, and machine learning.

GIET welcomes the young and dynamic technocrats into the field of Artificial Intelligence and Machine Learning.


To be a renowned department for imparting education in the specialized domain of Artificial Intelligence and Machine Learning and in moulding students into professional engineers.


    Develop professionals who are skilled in the area of artificial intelligence by imparting knowledge in cutting edge areas like image processing, speech recognition, natural language processing, knowledge representation, expert systems, machine learning, deep learning, etc.

    Impart quality and value-based education and contribute towards innovation in these areas of computing.

    Organize conferences, seminars, workshops, short term trainings, extra- and co-curricular activities in these areas.

    Apply new advances using high performance computing hardware and software.

    Establish centre of excellence in interdisciplinary areas of computing, especially in science and engineering applications.

    Program Outcomes (POs):

    After completion of the programme, the under graduate in Computer Science and Engineering (Artificial Intelligence and Machine Learning) will be able to:

    1: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

    2: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

    3: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.

    4: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.

    5: Create, select, and apply appropriate techniques, resources, and modern engineering and AIMLapplications including prediction and modeling to complex engineering activities with an understanding of the limitations

    6: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.

    7: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development

    8: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

    9: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings

    10: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.

    11: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

    12: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

    Program Educational Objectives  (PEOs):

    1. To apply appropriate theory, practices, and tools to provide solution for real-world challengesinvolving multidisciplinary/interdisciplinary areas.

    2. To function effectively in the workplace for professional growth or pursue higher education in leading institutions in the specialized areas of Artificial Intelligence & Machine Learning.

    3. To adapt, contribute and innovate new technologies in the key domains of Artificial Intelligence & Machine Learning for application in societal development, industrial growth and academic research.

      Program Specific Outcomes (PSO)

      PSO1. Apply the capabilities in the areas of Health Care, Education, Agriculture, Intelligent Transport,Environment,Smart Systems, Societal Needs, etc.and in other multi-disciplinary area of science and engineering domains.

      PSO2. Demonstrate engineering practice learned through industry internship to solve live problems in various domains.